With the advancements in the field of computer vision and range data processing, the visualization of the objects in a real-world environment is gaining popularity. The information extracted from the digital modelling of an object, surface or environment is used to derive meaningful interpretations. A digital representation of the environment have useful application in many fields, such as digital imaging, computer animation, special-effects in film, prototype imaging in marketing and product development, topography, reconstructive and plastic surgery, dentistry, industrial design, anthropology, milling and object production, biology, internal medicine, air traffic control management (for example, to model airspace surrounding an airport), architecture (for example, for modelling building, bridges, and so forth), military (for example, to depict topographical models of battlefields), and the like.
Several techniques have been developed to digitally represent an environment. Typically, devices such as Light Detection and Ranging (LIDAR) sensors are employed for capturing the objects of an environment. However, capturing a complete environment generally requires multiple range images from different viewpoints. Once these images are acquired, the various images must be combined (registered) either manually; or by utilizing algorithms, such as the Iterative Closest Point (ICP) algorithm to align two related captured images (or, point clouds), that are combined together to represent the environment. Such algorithms employ various techniques known in the art for alignment of two or more captured images to obtain the complete environment. However, the conventional techniques employed for alignment do not provide a measure of the accuracy achieved after registration. This might lead to unreliable data representing the environment in addition this might lead to wasted computing resources since storing unreliable data consumes storage space unnecessarily. Further if unreliable data is used for end application such as automatic vehicle it might lead accidents.
Therefore, in the light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with the alignment of two captured point clouds.